The genome-wide association studies (GWAS) have successfully identified a number of single nucleotide polymorphisms (SNPs) associated with melanoma risk. However, the traditional GWASs focus only on marginal effects of individual markers and have incorporated external functional information only after identifying robust statistical associations, which often miss relatively small effects conferred by most genetic variants. The pathway-based approaches, which evaluate the cumulative contribution of genes within biological pathways, may help collect the modest signals embedded in GWASs and identify the disease-related pathways on a pathway level. Though, the traditional pathway analyses simply assign the SNPs into nearby genes based on physical location, which may introduce numerous false positive associations due to multiple testing on non- functional SNPs and mis-annotate the SNPs regulating gene expression in distance. GWASs on gene expression that study the genetic variants regulating gene expression at a genomic scale have identified thousands of expression quantitative trait loci (eQTLs) that affect gene expression. Defining the eQTLs and assigning them into the genes that they regulate may help functionally annotate SNPs and increase the enrichment of functional variants in the biological pathways. The selection of the eQTLs in the pathways identified by pathway analysis for replication may increase the likelihood of targeting true signals than by chance. The integration of eQTLs of liver and adipose tissues into the pathway analysis for the GWAS of type 2 diabetes has successfully identified several disease-related pathways. More recently, a GWAS on global gene expression of the skin has systematically generated skin eQTLs. The goal of the current application is to assess the associations of biological pathways with melanoma risk by integrating the skin eQTLs into the pathway analysis for melanoma GWAS in the discovery stage and to validate the associations of specific loci within the identified pathways in the replication stage. Mediatio analysis on potential intermediate phenotypes will be conducted to investigate the etiological contribution of the identified pathways/SNPs. We plan to use a nested melanoma case-control study of 420 melanoma cases and 2,284 controls in two large, well- characterized cohorts, the Nurses' Health Study and the Health Professionals Follow-up Study in the discovery stage, and use a melanoma case-control study of 1,804 melanoma cases and 1,026 controls from the MD Anderson Cancer Center in the replication stage. All the cases and controls have been previously genotyped on Illumina SNP chips. The existing GWAS genotype data give us a cost-effective opportunity to apply the new approach to melanoma research. Our proposed study would be the first to combine the genetics of gene expression and functional classification of genes as prior information to apply in melanoma GWAS. This innovative work will utilize the GWAS data to a greater extent. Findings from this study will identify the genetic variants with modest effects from the GWAS data and provide new insights into the etiology of melanoma.